The mutation space of spatially conserved (MSSC) amino acid residues is a protein structural quantity developed and described in this work. The MSSC quantifies how many mutations and which different mutations, i.e., the mutation space, occur in each amino acid site in a protein. The MSSC calculates the mutation space of amino acids in a target protein from the spatially conserved residues in a group of multiple protein structures. Spatially conserved amino acid residues are identified based on their relative positions in the protein structure. The MSSC examines each residue in a target protein, compares it to the residues present in the same relative position in other protein structures, and uses physicochemical criteria of mutations found in each conserved spatial site to quantify the mutation space of each amino acid in the target protein. The MSSC is analogous to scoring each site in a multiple sequence alignment but in three-dimensional space considering the spatial location of residues instead of solely the order in which they appear in a protein sequence. MSSC analysis was performed on example cases, and it reproduces the well-known observation that, regardless of secondary structure, solvent-exposed residues are more likely to be mutated than internal ones. The MSSC code is available on GitHub: "https://github.com/Cantu-Research-Group/Mutation_Space".
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http://dx.doi.org/10.1021/acsomega.3c01473 | DOI Listing |
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Key Laboratory of Mariculture, Ministry of Education (KLMME), Ocean University of China, Qingdao, 266003, China.
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View Article and Find Full Text PDFSoft Matter
January 2025
Department of Mechanical Engineering & Materials Science, Washington University, St. Louis, USA.
Epithelial cell collectives migrate through tissue interfaces and crevices to orchestrate development processes, tumor invasion, and wound healing. Naturally, the traversal of cell collective through confining environments involves crowding due to narrowing spaces, which seems tenuous given the conventional inverse relationship between cell density and migration. However, the physical transitions required to overcome such epithelial densification for migration across confinements remain unclear.
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Novo Nordisk Research Center Seattle, Novo Nordisk A/S, Seattle, Washington, USA.
We present PepFuNN, a new open-source version of the PepFun package with functions to study the chemical space of peptide libraries and perform structure-activity relationship analyses. PepFuNN is a Python package comprising five modules to study peptides with natural amino acids and, in some cases, sequences with non-natural amino acids based on the availability of a public monomer dictionary. The modules allow calculating physicochemical properties, performing similarity analysis using different peptide representations, clustering peptides using molecular fingerprints or calculated descriptors, designing peptide libraries based on specific requirements, and a module dedicated to extracting matched pairs from experimental campaigns to guide the selection of the most relevant mutations in design new rounds.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Physics and Astronomy, University of California, Los Angeles, CA 90095.
The course of evolution is strongly shaped by interaction between mutations. Such epistasis can yield rugged sequence-function maps and constrain the availability of adaptive paths. While theoretical intuition is often built on global statistics of large, homogeneous model landscapes, mutagenesis measurements necessarily probe a limited neighborhood of a reference genotype.
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Private Practice of Plastic Surgery, Saint Petersburg, FL 33710, USA.
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